algebra

Jax Julia for python 2020-09-15 – 2022-06-22

Learning graphical models from data Also, causal discovery, structure discovery 2017-09-20 – 2022-05-18

Graph neural nets 2020-09-16 – 2022-05-18

Numerical PDE solvers 2016-03-01 – 2022-05-02

Causal graphical model reading group 2022 Causal inference 2022-04-01 – 2022-04-29

SLAM Simultaneous Location and Mapping 2014-11-25 – 2022-04-28

Vecchia factoring of GP likelihoods Ignore some conditioning in the dependencies and attain a sparse cholesky factor for the precision matrix 2022-04-27

Basis-functions in Gaussian process regression a.k.a Fixed Rank Kriging, basis function regression, weight space, spatial random effects 2022-02-22 – 2022-04-21

Stationary Gamma processes 2019-10-14 – 2022-04-08

Particle belief propagation Graphical inference using empirical distribution estimates 2014-07-25 – 2022-04-08

Particle Markov Chain Monte Carlo Particle systems as MCMC proposals 2014-07-25 – 2022-04-08

Orthonormal and unitary matrices Energy preserving operators, generalized rotations 2019-10-22 – 2022-04-05

Matrix calculus 2018-07-09 – 2022-04-04

Partition-valued random variates 2022-04-01

Belief propagation 2014-11-25 – 2022-03-31

Gaussian belief propagation Least squares at maximal elaboration 2014-11-25 – 2022-03-28

Multivariate Gamma distributions 2019-10-14 – 2022-03-14

Automatic differentiation in Julia 2016-07-27 – 2022-03-09

Causal inference on DAGs Confounding! This scientist performed a miracle graph surgery intervention and you won’t believe what happened next 2016-10-26 – 2022-03-08

Interaction effects are probably what we want to estimate 2022-01-25 – 2022-03-04

Fun with rotational symmetries 2021-01-29 – 2022-03-03

Conditional expectation and probability 2020-02-04 – 2022-02-25

Learning with conservation laws, invariances and symmetries 2020-04-11 – 2022-02-25

Visualising probabilistic graphical models Also related models, such as Neural nets 2018-03-29 – 2022-02-18

Message-passing algorithms in graphical models Cleaving reality at the joint, then summing it at the marginal 2014-11-25 – 2022-02-17

Factor graphs 2019-12-16 – 2022-02-09

Probabilistic graphical models 2014-08-05 – 2022-02-08

Random graphical models Causality in amongst confusion 2021-10-26 – 2022-02-07

Causality via potential outcomes Neyman-Rubin, counterfactuals, conditional treatment effects, and related tricks 2016-10-26 – 2021-12-10

Causal inference in highly parameterized ML 2020-09-18 – 2021-12-10

Random rotations 2021-05-18 – 2021-12-01

Gaussian Processes as stochastic differential equations Imposing time on things 2019-09-18 – 2021-11-25

External validity and dataset shift Also transfer learning, learning under covariate shift, transferable learning, domain adaptation etc 2020-10-17 – 2021-11-03

Spectral graph theory Linear signals on graphs 2014-11-24 – 2021-10-27

Neural music synthesis 2016-01-15 – 2021-10-14

Fun with determinants Especially Jacobian determinants 2011-04-06 – 2021-10-12

Mathematica 2011-04-06 – 2021-10-08

Multilinear algebra Outer products, tensors, einstein summation 2021-10-08

The Gaussian distribution The probability distribution that you give up and use in the end 2016-06-27 – 2021-10-03

Arpeggiate by numbers Workaday automatic composition and sequencing 2015-01-07 – 2021-09-20

Automatic differentiation 2016-07-27 – 2021-08-05

Algebraic probability If you liked it then you prob’ly put a ring on it 2017-06-15 – 2021-06-24

Isotropic random vectors 2011-08-10 – 2021-05-24

Randomized low dimensional projections 2021-03-12 – 2021-05-24

Computational symbolic mathematics Cheating at calculus exams 2016-10-13 – 2021-05-11

Causal inference in the continuous limit 2021-02-17

Partial differential equations 2021-01-27 – 2021-02-01

Tensor decompositions 2016-08-15 – 2020-11-19

Tensor regression 2020-11-19

Efficient factoring of GP likelihoods 2020-10-16 – 2020-10-26

Independence, conditional, statistical 2016-04-21 – 2020-09-13

Causal graphical model reading group 2020 An introduction to conditional independence DAGs and their use for causal inference. 2020-08-30 – 2020-09-03

Causal Bayesian networks Staged tree models, probability trees …Causalan Bayesian networks 2020-11-01 – 2020-09-01

Mathematics of textiles 2019-10-14 – 2020-08-20

MAPLE An OK computer algebra system 2020-05-19

Directed graphical models 2017-09-20 – 2020-05-13

Analysis/resynthesis of audio 2016-01-15 – 2020-04-09

Kernel approximation 2016-07-27 – 2020-03-06

(Reproducing) kernel tricks 2014-08-18 – 2020-01-20

Audio source separation 2019-11-04 – 2019-11-26

Tunings 2015-10-29 – 2019-11-18

Undirected graphical models 2017-09-20 – 2019-10-28

Inner product spaces The most highly developed theory of squaring things 2019-01-01 – 2019-02-11

Normed spaces 2019-01-01 – 2019-01-04

Linear algebra If the thing is twice as big, the transformed version of the thing is also twice as big. {End} 2011-04-06 – 2018-08-07

Musical metrics and manifolds 2014-09-26 – 2017-03-27

Functional equations Putting the funk in functions 2017-02-06 – 2017-02-19

Differential geometry, geometric algebra etc 2014-11-27 – 2016-10-13

Matrix norms, divergences, metrics 2016-06-03 – 2016-06-15

Category theory 2011-11-25 – 2016-04-18

Expectation maximisation 2014-08-17 – 2016-04-17

Coarse graining 2014-11-11 – 2015-12-02

Elliptical distributions 2015-06-23

Sigma algebras, probability spaces, measure theory The scaffolding of randomness 2015-06-20

Algebra I would like to learn 2014-10-15 – 2014-11-22